Furniture Extrac-on From Designed Home Decora-on and its Matching Guang Yang 1 , Chunliang Zheng 2 Department of Energy Resources Engineering 1 , Department of Electrical Engineering 2 , Stanford University Motivation Work Flow & Methodology Related Work • Parse furniture items from designed indoor scheme and find similar ones for users’ own decoration in laptop. • Use a handy android mobile application to quickly get information of the furniture items of interest in real life . Android Client Feature Matching / Image Retrieval Image Segmenta5on Object Recogni5on Server 1. Harris Keypoint detec5on 2. Watershed. 3. Coutours based. SVM classifiers. Matlab Contour based shape matching MexOpenCV Vlfeat Experimental Results 1. MexOpenCV library, Kota Yamaguchi, Stony Brook University 2. Caltech 101 Object Recognition, L. Fei-Fei, R. Fergus and P. Perona, CalTech University 3. Contour Correspondence via Colony Optimization, Oliver van Kaick, Simon Fraser University 4. Berkeley Segmentation Benchmark, UC Berkeley Intermediate Results Right: Watershed Left: Harris Keypoint Detection Combining three segmenta5on techniques, we get preKy nice results.(shown in demo) Contour shape matching is computa5onal efficient and works properly for furniture matching.